Search a local knowledge database with full-text queries. Filter results by agent or category and set a result limit to retrieve relevant stored knowledge.
Full-text search in knowledge database
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. | |
| query | Yes | Search query. | |
| agent_id | No | Optional agent filter | |
| category | No | Category filter or category to store. |
Changes observed during successful MCP inspections.
v0.1.0-alpha.29Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It indicates a read-style search operation, but says nothing about result ranking, pagination, permissions, rate limits, or whether it returns snippets versus full documents.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no wasted words. It immediately communicates the core operation and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema fully covers the input parameters, and the tool is a relatively simple search operation. However, with no output schema and no annotations, the description does not explain the return format or result behavior, leaving some context for the agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters including query, limit, agent_id, and category. The description adds no parameter-level meaning beyond what is already in the schema, making the baseline 3 appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Full-text search') and resource ('knowledge database'), so the agent knows this is a search operation. It does not explicitly differentiate from sibling tools such as hb_kb_list or hb_kb_get, but the word 'search' distinguishes it enough to infer its role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives like hb_kb_list for enumeration or hb_kb_get for direct retrieval. The agent must infer that it is for query-based search over the knowledge base.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.